Sparse GP approximation has been explored extensively to handle large datasets [1]}.
These approximations range from choosing subset of data, to making conditional assumptions on the joint prior using inducing datapoints.
While powerful, sparse GP approximations can lack analytical guarantees
[2]}.
The use of localized GP regressions to model local dynamics has been studied for model learning and control [3]}, [4]},
and it is shown that they can outperform sparse GP approximations if intelligent data partitioning is used [5]}.
Although they have been used in various control settings, formal online synthesis using GPs remains an open challenge.
